EE2211 – Introduction to Machine Learning
(2024-present)

This course introduces students to various machine learning concepts and applications, and the tools needed to understand them. Topics include supervised and unsupervised machine learning techniques, optimization, overfitting, regularization, cross-validation and evaluation metrics. The mathematical tools include basic topics in probability and statistics, linear algebra, and optimization. These concepts will be illustrated through various machine-learning techniques and examples.

Role: Tutor

EE2211 Link to NUSMODS